Smoothest paths for different settings of EventStudy
We construct event studies using different numbers of leads and lags.
We solve for the smoothest path in each case.
Summary data
A summary csv can be found at data_paths.csv. Recall that the
order of the computed polynomial equals order+1.
- The solver converges in all 72 cases.
- A computation is successful if the absolute difference between the
Wald critical value and the Wald optimal value is less than 0.1. There
were 41 successes.
Order found and number of successes, by outcome:
knitr::kable(
dt[, .(Num_found = .N,
Num_success = sum(success)),
by = .(yvar, order)]
)
| y_smooth_m |
1 |
7 |
7 |
| y_smooth_m |
2 |
18 |
3 |
| y_smooth_m |
3 |
10 |
10 |
| y_smooth_m |
4 |
1 |
1 |
| y_jump_m |
4 |
3 |
3 |
| y_jump_m |
5 |
10 |
7 |
| y_jump_m |
6 |
16 |
8 |
| y_jump_m |
7 |
6 |
1 |
| y_jump_m |
8 |
1 |
1 |
